Filters








5,454 Hits in 6.0 sec

The history of digital spam

Emilio Ferrara
2019 Communications of the ACM  
After providing a taxonomy of spam, and its most popular applications emerged throughout the last two decades, I will review technological and regulatory approaches proposed in the literature, and suggest  ...  Furthermore, when spam is carried out with the intent to deceive or influence at scale, it can alter the very fabric of society and our behavior.  ...  research collaborations and discussions on the topics of this work.  ... 
doi:10.1145/3299768 fatcat:ht45pgouvfhjnaka2uxqv4nahm

Consequences of Connectivity

Kurt Thomas, Frank Li, Chris Grier, Vern Paxson
2014 Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security - CCS '14  
In this study we expose the serious large-scale threat of criminal account hijacking and the resulting damage incurred by users and web services.  ...  We develop a system for detecting large-scale attacks on Twitter that identifies 14 million victims of compromise.  ...  Detecting Hijacked Accounts Our approach for detecting hijacked accounts builds on a large body of prior work for characterizing spam and abuse in social networks.  ... 
doi:10.1145/2660267.2660282 dblp:conf/ccs/ThomasLGP14 fatcat:w74xjm56wfgevpfblzppnztu7u

Early Detection of Outgoing Spammers in Large-Scale Service Provider Networks [chapter]

Yehonatan Cohen, Daniel Gordon, Danny Hendler
2013 Lecture Notes in Computer Science  
Our empirical evaluation of ErDOS is based on a real-life data-set collected by an email service provider, much larger than data-sets previously used for outgoing-spam detection research.  ...  We present ErDOS, an Early Detection scheme for Outgoing Spam. The detection approach implemented by ErDOS combines content-based detection and features based on inter-account communication patterns.  ...  New approaches are therefore needed in order to efficiently detect outgoing spam in large ESP environments. Our emphasis in this work is on early detection of spamming accounts hosted by ESPs.  ... 
doi:10.1007/978-3-642-39235-1_5 fatcat:rdzqaacomrh5ljy2joenazqh2u

A Study on Evolution of Email Spam Over Fifteen Years

De Wang, Danesh Irani, Calton Pu
2013 Proceedings of the 9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing  
Moreover, we extract sender-to-receiver IP routing networks from email spam and perform network analysis on it.  ...  Also, we investigate topic drift by applying topic modeling on the content of email spam.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or other funding  ... 
doi:10.4108/icst.collaboratecom.2013.254082 dblp:conf/colcom/WangIP13 fatcat:2emmqytqb5eobody4atkurfxeu

Is Email Business Dying?: A Study on Evolution of Email Spam Over Fifteen Years

De Wang, Danesh Irani, Calton Pu
2014 EAI Endorsed Transactions on Collaborative Computing  
In this paper, we analyze email spam trends on Spam Archive dataset, which contains 5.5 million spam emails over 15 years (1998 -2013).  ...  With the increasing dedication and sophistication of spammers, email spam is a persistent problem even today.  ...  study on large scale real data.  ... 
doi:10.4108/cc.1.1.e3 fatcat:ozdqb2g37bceppfrzugwn2r7qq

The Dark Menace

Rui Miao, Rahul Potharaju, Minlan Yu, Navendu Jain
2015 Proceedings of the 2015 ACM Conference on Internet Measurement Conference - IMC '15  
In this paper, using three months of NetFlow data in 2013 from a large cloud provider, we present the first large-scale characterization of inbound attacks towards the cloud and outbound attacks from the  ...  We investigate nine types of attacks ranging from network-level attacks such as DDoS to application-level attacks such as SQL injection and spam.  ...  This work is supported in part by the NSF grants CNS-1423505, CNS-1413972, and DHS-D15PC00184.  ... 
doi:10.1145/2815675.2815707 dblp:conf/imc/MiaoPYJ15 fatcat:2fotyt6cmvcupdcbhmw45httoq

The Abuse Sharing Economy: Understanding the Limits of Threat Exchanges [chapter]

Kurt Thomas, Rony Amira, Adi Ben-Yoash, Ori Folger, Amir Hardon, Ari Berger, Elie Bursztein, Michael Bailey
2016 Lecture Notes in Computer Science  
fake account registration, malicious hosting, and other forms of automated abuse.  ...  We estimate the scale of end hosts controlled by attackers, expose underground biases that skew the abuse perspectives of individual web services, and examine the frequency that criminals re-use the same  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors.  ... 
doi:10.1007/978-3-319-45719-2_7 fatcat:bptjcrmedjf23ffw2xtytvjp2y

Trust Aware System for Social Networks: A Comprehensive Survey

Manasa S., Manjula S., Venugopal K.
2017 International Journal of Computer Applications  
Hence to provide a trustworthy system and to enable real users activities a review on different methods to achieve trustworthy social networking systems are examined in this paper.  ...  Users on social networks are authorised by providing the personal data.  ...  spam, spamas-a-service Large scale spam maintenance is tedious.  ... 
doi:10.5120/ijca2017913307 fatcat:2xc5xryfcfewhnf7hjg5jhqjaa

SocialFilter: Collaborative Spam Mitigation using Social Networks [article]

Michael Sirivianos, Xiaowei Yang, Kyungbaek Kim
2009 arXiv   pre-print
Our proposal, SocialFilter, aims to achieve the trustworthiness of centralized security services and the wide coverage, responsiveness and inexpensiveness of large-scale collaborative spam mitigation.  ...  We propose a large-scale distributed system that enables clients with no email classification functionality to query the network on the behavior of a host.  ...  Because of this early detection, SocialFilter can block more spam emails when the number of spammers are bigger.  ... 
arXiv:0908.3930v1 fatcat:px5dmjgrtjdqnnhatj5n27k4xi

EVILCOHORT: Detecting Communities of Malicious Accounts on Online Services

Gianluca Stringhini, Pierre Mourlanne, Grégoire Jacob, Manuel Egele, Christopher Kruegel, Giovanni Vigna
2015 USENIX Security Symposium  
EVILCOHORT only needs the mapping between an online account and an IP address to operate, and can therefore detect malicious accounts on any online service (webmail services, online social networks, storage  ...  We evaluated EVILCOHORT on multiple online services of different types (a webmail service and four online social networks), and show that it accurately identifies malicious accounts.  ...  Acknowledgments This work was supported by the Office of Naval Research (ONR) under grant N00014-12-1-0165, the Army Research Office (ARO) under grant W911NF-09-1-0553, the Department of Homeland Security  ... 
dblp:conf/uss/StringhiniMJEKV15 fatcat:uh4xxqhszfgfxotvuwojsnelfe

Detecting and characterizing social spam campaigns

Hongyu Gao, Jun Hu, Christo Wilson, Zhichun Li, Yan Chen, Ben Y. Zhao
2010 Proceedings of the 10th annual conference on Internet measurement - IMC '10  
In this paper, we present an initial study to quantify and characterize spam campaigns launched using accounts on online social networks.  ...  We submit each unique URL from our dataset to each service in order to account for discrepancies between the coverage of different blacklists.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1145/1879141.1879147 dblp:conf/imc/GaoHWLCZ10 fatcat:u7ywdh5bfbao5puzwv77jiluqe

Detecting and characterizing social spam campaigns

Hongyu Gao, Jun Hu, Christo Wilson, Zhichun Li, Yan Chen, Ben Y. Zhao
2010 Proceedings of the 17th ACM conference on Computer and communications security - CCS '10  
In this paper, we present an initial study to quantify and characterize spam campaigns launched using accounts on online social networks.  ...  We submit each unique URL from our dataset to each service in order to account for discrepancies between the coverage of different blacklists.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1145/1866307.1866396 dblp:conf/ccs/GaoHWLCZ10 fatcat:6iujqjayhfc4laxufalijxxw3m

Detecting Fake Followers in Twitter: A Machine Learning Approach

Ashraf Khalil, Hassan Hajjdiab, Nabeel Al-Qirim
2017 International Journal of Machine Learning and Computing  
The services that this market provides include: the sale of fraudulent accounts, affiliate programs that facilitate distributing Twitter spam, as well as a cadre of spammers who execute large scale spam  ...  In addition, twitter users have started to buy fake followers of their accounts. In this paper we present machine learning algorithms we have developed to detect fake followers in Twitter.  ...  One of the early efforts to detect and fight spam and spammers on Twitter was by Fabricio et al. [1] .  ... 
doi:10.18178/ijmlc.2017.7.6.646 fatcat:nalufabfhnbhzauaqf2zqj6cyu

Adapting Social Spam Infrastructure for Political Censorship

Kurt Thomas, Chris Grier, Vern Paxson
2012 USENIX Workshop on Large-Scale Exploits and Emergent Threats  
We find that miscreants leveraged the spam-as-a-service market to acquire thousands of fraudulent accounts which they used in conjunction with compromised hosts located around the globe to flood out political  ...  In this paper, we undertake an in-depth analysis of the infrastructure and accounts that facilitated the attack.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.  ... 
dblp:conf/leet/ThomasGP12 fatcat:jsnooworqzcx7c6uzrrfxzdclq

Follow Spam Detection based on Cascaded Social Information [article]

Sihyun Jeong, Giseop Noh, Hayoung Oh, Chong-kwon Kim
2016 arXiv   pre-print
In the last decade we have witnessed the explosive growth of online social networking services (SNSs) such as Facebook, Twitter, RenRen and LinkedIn.  ...  Therefore, detecting spammers has become an urgent and critical issue in SNSs. This paper deals with Follow spam in Twitter.  ...  Spam refers to unwanted messages from unknown sources (attackers). One of the major negative aspects of SNS is spam. In the early Internet era, spam appeared in emails or SMS (short message service).  ... 
arXiv:1605.00448v1 fatcat:w6pwgwbz3feg5nin24ohaeegya
« Previous Showing results 1 — 15 out of 5,454 results